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Mingyang Lu

Researcher at University of Manchester

Publications -  65
Citations -  1351

Mingyang Lu is an academic researcher from University of Manchester. The author has contributed to research in topics: Eddy current & Eddy-current sensor. The author has an hindex of 17, co-authored 62 publications receiving 866 citations. Previous affiliations of Mingyang Lu include Tianjin University of Science and Technology.

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Determination of the Magnetic Permeability, Electrical Conductivity, and Thickness of Ferrite Metallic Plates Using a Multifrequency Electromagnetic Sensing System

TL;DR: An inverse method was developed which can, in principle, reconstruct arbitrary permeability, conductivity, thickness, and lift-off with a multifrequency electromagnetic sensor from inductance spectroscopic measurements and shows for the first time that the inductanceSpectra can be inverted in practice to determine the key values with a relative error of less than 5% during the thermal processing of metallic plates.
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Reducing the Lift-Off Effect on Permeability Measurement for Magnetic Plates From Multifrequency Induction Data

TL;DR: In this paper, a modified index, termed as the compensated zero-crossing frequency, can be obtained from the measured multifrequency inductance spectral data using the algorithm developed in this paper.
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A Novel Compensation Algorithm for Thickness Measurement Immune to Lift-Off Variations Using Eddy Current Method

TL;DR: An algorithm can compensate for this variation and produce an index that is linked to the thickness, but is virtually independent of lift-off, which can be obtained from the measured multifrequency inductance spectral data using the algorithm developed in this paper.
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Thickness Measurement of Metallic Plates With Finite Planar Dimension Using Eddy Current Method

TL;DR: A modified analytical solution based on the Dodd–Deeds model is proposed, which has introduced a new initial integration point instead of 0 for the analytical inductance of the finite-size metallic plate.
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Textile-Based Capacitive Sensor for Physical Rehabilitation via Surface Topological Modification.

TL;DR: A textile-based capacitive sensor with flexible, comfortable, and durable properties has been demonstrated and has successfully been used for real-time monitoring human breathing, speaking, blinking and joint motions during physical rehabilitation exercises.